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https://issues.apache.org/jira/browse/CASSANDRA-13780?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16136849#comment-16136849
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Kevin Rivait commented on CASSANDRA-13780:
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thank you Kurt
reg 1.
On our DEV environment (1 DC) we did set streamthroughput to zero on all
nodes including the new node with no observed change in throughput.
On our PROD environment ( 2 DCs) we set streamthroughput to zero on all nodes
in the DC we were adding the node in. We observed streaming from all nodes in
the local DC.
We cannot achieve the default 200Mb/s streamthroughput per node
Our most recent experimental observation is the total streamthroughput for the
whole cluster is ~80Mb/s regardless of the number of nodes in the cluster. As
we add more nodes, the throughput of each node drops such that the sum total
remains ~ 80Mb/s
Are there other parameters or bottlenecks that can reduce streaming throughput
of each node?
reg 2.
You are correct.
We went back and dumped the SSTABLE max/min dates and verified that the buckets
older than TTL and GCGS are in fact being dropped.
thank you
Kevin
> ADD Node streaming throughput performance
> -----------------------------------------
>
> Key: CASSANDRA-13780
> URL: https://issues.apache.org/jira/browse/CASSANDRA-13780
> Project: Cassandra
> Issue Type: Improvement
> Components: Core
> Environment: Linux 2.6.32-696.3.2.el6.x86_64 #1 SMP Mon Jun 19
> 11:55:55 PDT 2017 x86_64 x86_64 x86_64 GNU/Linux
> Architecture: x86_64
> CPU op-mode(s): 32-bit, 64-bit
> Byte Order: Little Endian
> CPU(s): 40
> On-line CPU(s) list: 0-39
> Thread(s) per core: 2
> Core(s) per socket: 10
> Socket(s): 2
> NUMA node(s): 2
> Vendor ID: GenuineIntel
> CPU family: 6
> Model: 79
> Model name: Intel(R) Xeon(R) CPU E5-2630 v4 @ 2.20GHz
> Stepping: 1
> CPU MHz: 2199.869
> BogoMIPS: 4399.36
> Virtualization: VT-x
> L1d cache: 32K
> L1i cache: 32K
> L2 cache: 256K
> L3 cache: 25600K
> NUMA node0 CPU(s): 0,2,4,6,8,10,12,14,16,18,20,22,24,26,28,30,32,34,36,38
> NUMA node1 CPU(s): 1,3,5,7,9,11,13,15,17,19,21,23,25,27,29,31,33,35,37,39
> total used free shared buffers cached
> Mem: 252G 217G 34G 708K 308M 149G
> -/+ buffers/cache: 67G 185G
> Swap: 16G 0B 16G
> Reporter: Kevin Rivait
> Priority: Blocker
> Fix For: 3.0.9
>
>
> Problem: Adding a new node to a large cluster runs at least 1000x slower than
> what the network and node hardware capacity can support, taking several days
> per new node. Adjusting stream throughput and other YAML parameters seems to
> have no effect on performance. Essentially, it appears that Cassandra has an
> architecture scalability growth problem when adding new nodes to a moderate
> to high data ingestion cluster because Cassandra cannot add new node capacity
> fast enough to keep up with increasing data ingestion volumes and growth.
> Initial Configuration:
> Running 3.0.9 and have implemented TWCS on one of our largest table.
> Largest table partitioned on (ID, YYYYMM) using 1 day buckets with a TTL of
> 60 days.
> Next release will change partitioning to (ID, YYYYMMDD) so that partitions
> are aligned with daily TWCS buckets.
> Each node is currently creating roughly a 30GB SSTable per day.
> TWCS working as expected, daily SSTables are dropping off daily after 70
> days ( 60 + 10 day grace)
> Current deployment is a 28 node 2 datacenter cluster, 14 nodes in each DC ,
> replication factor 3
> Data directories are backed with 4 - 2TB SSDs on each node and a 1 800GB SSD
> for commit logs.
> Requirement is to double cluster size, capacity, and ingestion volume within
> a few weeks.
> Observed Behavior:
> 1. streaming throughput during add node – we observed maximum 6 Mb/s
> streaming from each of the 14 nodes on a 20Gb/s switched network, taking at
> least 106 hours for each node to join cluster and each node is only about 2.2
> TB is size.
> 2. compaction on the newly added node - compaction has fallen behind, with
> anywhere from 4,000 to 10,000 SSTables at any given time. It took 3 weeks
> for compaction to finish on each newly added node. Increasing number of
> compaction threads to match number of CPU (40) and increasing compaction
> throughput to 32MB/s seemed to be the sweet spot.
> 3. TWCS buckets on new node, data streamed to this node over 4 1/2 days.
> Compaction correctly placed the data in daily files, but the problem is the
> file dates reflect when compaction created the file and not the date of the
> last record written in the TWCS bucket, which will cause the files to remain
> around much longer than necessary.
> Two Questions:
> 1. What can be done to substantially improve the performance of adding a new
> node?
> 2. Can compaction on TWCS partitions for newly added nodes change the file
> create date to match the highest date record in the file -or- add another
> piece of meta-data to the TWCS files that reflect the file drop date so that
> TWCS partitions can be dropped consistently?
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